Enterprise Data Infrastructure
With End-to-End Ownership
Scalefocus composes and evolves enterprise data foundations across Lakehouse architecture, real-time pipelines, and governed data. Every AI and analytics initiative starts on solid ground, and you keep full ownership of the architecture and economics.
The Problem
Every Failed AI Initiative Has the Same Root Cause
80% of AI effort goes into wrangling data instead of building intelligence. Models trained on fragmented and stale data produce untrusted answers at scale. The signs are usually the same:
Numerous Systems, No Single Truth
ERP, CRM, and operational data live in silos that contradict each other.
Old Data for New Decisions
Batch jobs deliver insight hours after the right moment has passed.
Pilots That Never Reach Production
Every AI proof of concept starts from scratch, only to stall at handover.
Reports Nobody Trusts
When two dashboards show different numbers,
executives stop reading both.
What We Build
One Foundation, Five Layers
Lakehouse
Architecture
Platform for Every Workload
BI, machine learning, and generative AI on a single governed platform instead of three stacks glued together.
We design and implement Lakehouse architectures on Databricks, Snowflake, and Microsoft Fabric, with medallion-layered data and unified governance from the start.
Real-Time Data
Pipelines
Decide at the Speed of Events
We build streaming architectures on Kafka, Flink, Azure Event Hubs, and Snowpipe.
Fraud detection, dynamic pricing, IoT telemetry, and trading signals are all handled as events happen.
Enterprise
Integration
All Systems Connected in One Data Flow
Your data foundation is only as strong as its weakest link. We integrate ERP, CRM, billing, and operational systems through MuleSoft, API-led architectures, and event-driven layers.
The result is scalable, maintainable patterns.
Data
Modernization
Migrate Legacy Without Stopping the Business
Modernization shouldn’t mean freezing and starting from scratch.
We migrate data estates from legacy warehouses and on-prem systems incrementally to cloud and hybrid platforms. Old & new run in parallel until cutover is safe.
Data
Reliability
Data Your Board Can Sign Off on
Trust is an engineering outcome. We implement data quality frameworks, observability, lineage, and governance across Unity Catalog and Microsoft Purview.
With GDPR, NIS2, and DORA compliance, and built-in automated testing, the numbers in the boardroom match those in the warehouse.
Client Success Stories
Cutting Analytics
Lead Time
A Data Mesh and self-serve analytics platform lets domain teams publish trusted data products independently to reduce analytics lead time significantly.
Revamped Reporting
& Analytics
An event-driven pipeline with real-time triggers provides traders and analysts with insight as markets unfold, while a data quality framework ensures full visibility across every data series.
Open-Source Integration Layer Development
We replaced a proprietary integration platform for a US retail leader with an open-source layer that runs its entire omnichannel flow, significantly reducing licensing costs.
Data Platform Modernization
We modernized a drilling data platform for a leading Austrian energy technology company, achieving a 60x improvement in data processing speed.
Driving ESG & ML Innovation
Data governance across a fragmented logistics ecosystem tripled data testing speed and now powers CO2-neutrality decisions across the full supply chain.
Scalefocus’ Approach
Built by Us. Owned by You.
Most providers deliver a solution and retain control of it. We engineer data foundations where architecture, code, and economics are yours end-to-end.
Sovereign by Design
Your data, your platform, your operational logic. No dependency whatsoever after handover.
Platform-Certified, Platform-Neutral
Our deep partnerships with Databricks, Microsoft Azure, Snowflake, and MuleSoft enable us to recommend what fits your estate perfectly.
Lifecycle Ownership
We evolve the foundation as a living asset, or hand it to your team with the playbooks so they can do it themselves.
The Data Foundation Assessment
Know Where You Stand Within Days
A fixed-scope engagement. Senior data architects review your estate and deliver three things:
An AI-Readiness
Scorecard
Where your data foundation supports your AI ambitions, and where it might break.
A Target
Architecture
Lakehouse, streaming, and integration blueprint mapped to your actual systems.
A Roadmap
With TCO
Sequenced, costed, and built for incremental delivery. No disruption to what’s already running.
FAQ
Questions CIOs ask us.
Not always. A warehouse serves BI well but struggles with ML, unstructured data, and GenAI workloads. The assessment tells you whether to extend, augment, or replace. We've done all three.
First production workloads typically land in 8 to 12 weeks. Full estate migration is sequenced over months, with legacy and modern running in parallel. The business never stops.
Databricks, Snowflake, Microsoft Fabric and the Azure data stack, Kafka, MuleSoft, hybrid and on-prem estates. We recommend based on your landscape rather than a reseller agreement.
That's the default. We embed with your engineers, transfer the playbooks, and leave you in control. Lifecycle operations by Scalefocus are optional.
Everywhere, and that's the point. A governed Lakehouse with reliable, real-time data is the prerequisite for production AI. We also build the AI layer itself: